The Alternative Investment Management Association

Alternative Investment Management Association Representing the global hedge fund industry

Cultivating skill in a world lacking genius

By Simon Savage, Risk Specialist, GLG Partners, and Paul Gibson, Chief Tactical Writer, Man


First published in Q1 2013 edition


The following statement featured in the opening address at a prestigious annual conference for registered investment advisors in San Francisco in the mid-1990s:

“It is my contention that active management does not make sense theoretically and is not justified empirically.” Rex Sinquefeld

A whole raft of academic research has been conducted with the sole objective of refuting the value of active management. Many such studies seek only to demonstrate what basic mathematics already tells us. If participation in capital markets is a zero-sum game in which one can only profit at the expense of another, it is obvious that active management per se cannot beat the market. However, this does not preclude the possibility of the best managers outperforming on a consistent basis.

Consequently, it is far more objective to question why most fund managers fail to outperform the market and to use this as a basis for determining the infrastructure, support and culture that can and does promote the generation of above-average investment returns.

Based on analysis of reams of research, it is our contention that there are three main reasons that account for underperformance:

  • Managers of traditional, long-only funds appear to fear significantly underperforming their benchmark index more than they aspire to outperform it
  • Asset managers typically have an inflated belief in their own natural stock-picking ability (talent)
  • Deeply inherent psychological and behavioural biases can prevent managers from making rational decisions

Fear and aspiration

The asset management industry is dominated by so-called actively-managed funds which could more accurately be described as ‘closet trackers’. Funds falling into this category typically operate with a tracking error of around 3% and levy an average management fee of 1.5%.1 Researchers have attributed this penchant for quasi-indexation to a perception on the part of fund managers that their investors wish them to strictly control their tracking error relative to their given benchmark. Therefore guaranteed mediocrity is deemed more palatable than substantial underperformance; the latter prospect can clearly be mitigated by managing the fund with a tight tracking error.

However, the additional utility that can be generated by a fund manager is dependent not only on stock picking skill, but the ability and courage to reflect conviction in scaling portfolio positions. Low tracking errors are therefore clearly an impediment to value creation. Yet, as illustrated in the chart below, the tendency for managers to stymie their own performance potential appears to have become more dominant in recent years.

Significantly, the proportion of mutual fund assets managed with an active (or benchmark-differentiated) share of 80% or more fell from over 60% to around 20%2 during the course of the three decades analysed, while the percentage of passively or quasi-passively managed assets increased from 2% to around 50%.

More detailed analysis3 found that between 1985 and 2000 the average fund size increased more than sixfold, the mean number of portfolio assets more than doubled and the concentration in large cap (high beta) stocks rose sharply, making it increasingly difficult for fund managers to outperform their benchmarks. In the first few years of the new century the number of funds and the extent of large cap concentration both declined. However, the average fund size and number of holdings continued to rise, which is clearly counter-productive in terms of meeting performance objectives.

Consequently, it is not surprising that more recent analysis over 15 years4 shows that the median excess return of actively managed funds is -1.5%. In other words, the average actively-managed fund performs in line with its benchmark index on a gross-of-fees basis. Moreover, this also demonstrates the negative return asymmetry created by the combination of a low tracking error (e.g. 3%) and the typical 1.5% annual management fee. In such circumstances, the maximum net-of-fees performance is 1.5% and the minimum return level is -4.5%.

An increasing reluctance to deviate from the benchmark


Man Chart 4

Source: 'Active share and mutual fund performance', Antti Petajisto (2010)


In other words, the probability of a fund under-performing over any given period is three times greater than the probability of outperformance. Indeed, it cannot be a coincidence that the average performance level actually recorded over a 15-year period is precisely half way between the two possible extremes.

First conclusion: In order to enhance the prospects of alpha generation through stock picking, asset managers need to be encouraged to express real conviction in their stock selection. One way of achieving this is to provide them with the opportunity to operate within a risk framework that neutralises systematic exposures, thus ensuring that there is no motivation for asset managers to hold ‘benchmark makeweights’ that they have no strong view on.

“The very nature of fund evaluation may cause fund managers to hold many stocks in which they have little conviction.”5 Jonathan Berk and Richard Green

The perception of talent and overconfidence

“Genius is the work of human grit, not the product of superhuman grace.”6 Andrew Robinson

The asset management industry operates almost exclusively on the premise that successful stock picking is a product of talent. Not only is this almost certainly fallacious, the concept of worshipping talent is highly corrosive. As Matthew Syed, table tennis champion turned author and motivational speaker, astutely observes, ‘if we believe that talent is only marginally implicated in our future success, we are likely to persevere’.7 Clearly, Syed is seeking to inspire people to believe that anybody can do anything if they put enough effort in. However, the other side to this argument is that believing in our own talent constitutes a self-improvement disincentive.

Academic research also demonstrates that human beings typically display overconfidence (as illustrated below). However, this ‘overconfidence gap’ can be narrowed significantly when individuals are required to challenge their thought process by making a statement that contradicts their initial response or statements that both support and contradict it.

Overconfidence is an inherent and systematic bias…   


Man Chart 1

…which can be mitigated


Man Chart 2

Source: ‘Reasons for confidence’ Koriat, Lichtenstein and Fischhoff (1980)

Clearly, overconfidence is steeped in the assumption that a task is more straightforward than it actually is. Moreover, this assumption is typically based on a self-perception of intellectual superiority. In each case, improvement can be generated by challenging the initial assumption or perception, but not necessarily by devoting more time to gathering or expounding evidence in support of it (‘confirmation bias’).

In asset management terms, the existence of the overconfidence and confirmation biases in human beings is highly relevant; if we are all naturally prone to overconfidence it can clearly be exacerbated by positive affirmation. One such example of positive affirmation would be to recruit a fund manager with a sound track record, pay them a ‘golden hello’ in recognition of their exceptional talent and leave them to operate from a private office in isolation, where they can carry out confirmation-biased research on which to base their trades.

In fact, Carol Dweck, a social psychologist who has spent more than 30 years studying motivation, discovered that lauding an individual’s talent does not foster self-esteem and accomplishment, but has the opposite effect. She conducted an experiment9 in which children were given a test and, subsequently, half were praised for their intelligence and half for their effort.

The children were then given the option of taking either a harder test or an easier test. 90% of the children praised for effort chose the harder option, while the vast majority of those praised for their intelligence opted to take the easier test.

Dweck concluded that in praising one group for their intelligence she had fostered an ‘entity view’. They believed in their own intelligence but considered it fixed and stable and therefore did not want to risk looking unintelligent. This also made them prone to giving up easily.

Conversely, praising individuals for their endeavour encourages them to adopt an ‘incremental view’ or (‘growth mindset’). They see intelligence as malleable and are therefore incentivised by opportunities to better themselves, believing that increased learning and strategic development will increase their intelligence (or skill).

Second conclusion: We believe that asset managers are likely to make more-informed and better trading decisions if they work in an open environment of collaboration, in which their conclusions are challenged from a multiplicity of perspectives and where a growth mindset is positively encouraged.

The psychology of irrational decisions

“We are not only irrational, we can be predictably irrational.”10 Dan Ariely

In the preceding section, we sought to refute the notion that talent is the root of successful stock picking. In this respect, we feel that it is essential to distinguish between the terms ‘skill’ and ‘talent’. It is our firm belief that the best asset managers display considerable skill in portfolio construction and trading.

Indeed, this assertion is backed by a number of studies in which the authors seek to differentiate between the performance persistency of the best and worst managers, rather than dealing with the entire universe of ‘active managers’ at the aggregate level.

For example, Kosowski, Timmermann, Wermers and White11 found evidence demonstrating that the top decile of performance can be characterised as persistent, skill-based alpha. Similarly, Gray and Kern12 found ‘overwhelming evidence’ that the hedge fund managers in their sample displayed stock-picking skills. Moreover, they concluded that the rewards for finding good managers were “certainly high enough to justify the increased fees”.

Clearly, luck has a role to play in the formation of short-term track records, while instinct is a vital attribute for anybody involved in trading. However, the importance of experience should never be underestimated. As the multiple best-selling author Malcolm Gladwell puts it, “instinct is the gift of experience. If you have no experience, then your instincts aren’t any good”.13

Moreover, we believe that skilled and experienced asset managers can be coached to be more effective stock pickers. Daniel Coyle, a New York Times best-selling author, refers to hotbeds as “the blue print of high performance”14 Coyle spent years visiting the world’s greatest talent hotbeds in sports, arts and business that produce huge numbers of extraordinary performers. He found that the secret is in the specific, targeted methods of training and motivation used in these hotbeds to build the high-speed neural circuitry that underlies all greatness.

Similarly, at GLG, we are seeking to create our own hotbed, partly facilitated through the use of an objective feedback mechanism. This helps our managers to mitigate the behavioural biases that typically inhibit the performance of others, especially in pressure situations.

Managers should run winners and cut losers, but…


Man Chart 3
Source: Man database. Schematic illustration.


The chart above illustrates a typical exit return trace (i.e. how a stock performs before and after the decision to dispose of the holding). Intuitively, we know that the best results will be achieved by running winners and cutting losers. However, as human beings we are naturally conditioned to do the opposite.

At the conscious level, there is a fairly straightforward explanation for this. When a trade is a winning one, we are acutely aware that we will not actually realise a profit until the position is sold. Therefore, we become extremely anxious as soon as the stock price begins to fall. Conversely, when a trade is losing money, we are psychologically reluctant to turn a paper loss into a real loss. In fact, academic research on the psychology of behavioural economics from the 1970s demonstrates that people fear losing money approximately twice as much as they enjoy winning it (‘loss aversion’)15.

In order to discover the extent to which the performance of asset managers is inhibited by such behavioural biases it is necessary to conduct extensive analysis. This is an onerous task but one that can provide a clear evaluation of how well managers construct their portfolios and time trades. Indeed, when evidence-based analysis is used appropriately, it can highlight the strengths and weaknesses of managers.

The establishment of rules then becomes a critical element in enabling an asset manager to stay true to their strengths. Moreover, these rules need to have more parameters than those required to simply stop losses; time thresholds, investment types, market environments and emotional states are all vital considerations. We know that all these factors can alter success and, as such, they should be constrained based on the evidence of the extent to which they affect an individual’s decision making.

Third conclusion: It is important to recognise that length of experience is of little value if fund managers remain unaware of their strengths and weaknesses. The process of providing and heeding objective and multifaceted feedback is essential in cultivating the skills of experienced managers, helping them become more consistently successful.

A performance-based culture

“The people who stand before kings (high achievers) are invariably the beneficiaries of hidden advances and cultural legacies that allow them to learn and make sense of the world in ways others cannot.” 18 Malcolm Gladwell

In conclusion, large parts of the asset management industry achieve disappointing results because they are not culturally-equipped to succeed. Thomas Edison reportedly first coined the phrase, “Genius is 1% inspiration and 99% perspiration” way back in 1903 and it has been published extensively since. Yet, for the most part, asset managers are still considered to have an innate talent that is denied to others or a superior intellect that requires no development.

Experiments in social psychology suggest that people who are lauded for their talent become scared of making mistakes for fear of looking unintelligent. If this mantra is applied to the asset management industry, ‘talented’ individuals are likely to construct portfolios that closely resemble their benchmarks. Statistical data confirms this.

As a consequence, the measure of success has become winning by not losing. While we have discovered evidence that many actively-managed portfolios are becoming even more aligned with their benchmarks, the self-defeating nature of quasi-tracking has been recognised for almost 40 years.19

Skill has to be carefully cultivated and individuals need to be nurtured in a supportive environment so that they are comfortable in taking high-conviction positions. If the systematic risk is managed on their behalf they can concentrate on constructing a portfolio solely of stocks that they have strong conviction in, rather than being distracted by the need to include benchmark makeweights.

However, we need to be wary that human beings can suffer from overconfidence and, like all good conspiracy theorists, we are susceptible to a ‘confirmation bias’ in our research efforts. To counter this we need to place asset managers in an open and challenging environment to ensure that key decisions are weighed up from a multiplicity of perspectives.

Finally, the best performing managers are those that run winners and cut losers. However, this concept is completely alien to the human psyche. Consequently, individuals need to be coached to overcome deeply-entrenched behavioural biases such as priming, cognitive ease and loss aversion. These biases can not only lead to weaker-than-expected performance, they contribute to market inefficiency and therefore create opportunities for those that are able to exploit the dislocations in valuations that arise from them.

As we have seen, there is a wealth of research into such psychological and behavioural traits but, in our experience, most asset management firms have not begun to confront the issue. Conversely, it is our contention that no active risk management framework can be complete unless it includes a process for addressing the behavioural biases inherent in poor decision making.

After all, under tight benchmark constraints and in an ‘entity mindset’, any good luck that contributes to successful stock picking is attributed to skill, while injudicious decisions that detract from performance are blamed on ‘difficult market conditions’. Instead, asset managers should focus on self-awareness and develop a growth mindset. Understanding that success or failure is derived from analysis of the underlying decision metrics, rather than solely being a function of the end product of realised returns, is essential.

Objective feedback relating to both winning and losing positions can foster a greater understanding of the fundamental question ‘How do I make money?’ The ability to answer this question provides asset managers with the potential to move away from a random, luck-influenced world and onto a path of repeatable, skill-based success.

Background to the research8

In 1980, researchers conducted a simple experiment in which subjects were asked to answer a series of multiple-choice questions, and provide an indication of the probability of the answer being correct (confidence).

Having discovered a systematic discrepancy between correctness and conviction (‘over confidence’), particularly at higher conviction levels, the researchers conducted a second experiment to assess the extent to which this dislocation could be reduced.

Firstly, the subjects were asked to write down a reason in support of their answer being correct (‘supporting’). Although this exercise yielded some improvement at lower confidence levels, it is simply a case of asking subjects to commit to paper the reason why they came to their conclusion. Consequently, it is not surprising that it yielded identical results at the 100% confidence level.

A second group of subjects were then asked to repeat the same process but to write down a reason why the answer given could be incorrect (‘contradictions’). This generated noticeable improvement, partly because it helped to counter a natural human tendency to ignore unsupportive information in reaching a conclusion (‘confirmation bias’).

The final group of subjects were asked to write down both a reason in support of their answer and one contradicting it (both). Interestingly, this group provided contradictory responses that, in some cases, confronted their supporting reasons. As illustrated in the second of the charts above, further improvement was clearly detectable at the highest conviction level. Consequently, it demonstrates that people can achieve better results if they take a disciplined approach to weighing the evidence before making a commitment.

Priming and cognitive ease

The concept of priming was first advanced in the 1970s.  It suggests that human judgment can be instantly biased by recent observation. For example, researchers conducted an experiment in which a sample of individuals was exposed to words related to kindness as part of an apparent language study. When subsequently asked to describe an individual, this group was far more disposed to use kindness-related adjectives than a second group which had received no such ‘priming’16.

From a fund management perspective, priming is significant because human beings rarely retrieve all relevant information, but merely what we consider to be ‘enough’, when making a judgment. This means that recent observations have a disproportionate influence in the decision-making process. Moreover, what is considered a ‘perception’ may in fact just be an expression of subconscious memory.

Noble prize-winner Daniel Kahneman began investigating the concept of cognitive ease in 1973 when he and his co-researcher Amos Tversky introduced the ‘availability heuristic’.17 They discovered that when people are asked to assess the frequency of a class or the probability of an event, they are biased by the ease with which instances or occurrences can be brought to mind.

Kahneman subsequently distilled a lifetime of research into his 2011 tome ‘Thinking, Fast and Slow’ in which he states that our cognitive process is split into two systems. The ‘fast’ system is intuitive and effort free, while the ‘slow’ system is based on conscious, deductive reasoning and hard work. Clearly, decisions in asset management should be based on the slow system, but the reality is that investment professionals can and do buy into ‘stories’ that instinctively feel right.


[1] ‘Are fund charges eating into your returns?’ Which [the consumer association of the UK] (2010).
[2] ‘The economic implications of passive investing’ Woolley and Bird (2003).
[3] ‘Best Ideas’ Cohen, Polk and Silli (2009). The study analysed year-end summary statistics of all actively-managed mutual funds detailed on Datastream (Thompson Financial) that contained at least five stocks and had total net assets exceeding USD 5 million.
[4] The calculation for the excess return of underperforming managers is based on the median return of value and growth managers over a 15-year period ending 31.12.2009. (Source of data: Vanguard, MorningStar and MSCI).
[5] From ‘Mutual fund flows and performance in rational markets’ (2004).
[6] From ‘Sudden genius?: The gradual path to creative breakthroughs’ (2010).
[7] From ‘Bounce’ (2010).
[8] ‘Reasons for confidence’ Koriat, Lichtenstein and Fischhoff (1980).
[9] ‘Self-theories: their role in motivation, personality and development’ (1999).
[10] From ‘Predictably irrational’ (2008).
[11] Can mutual fund ‘stars’ really pick stocks? New evidence from a bootstrap analysis’ (2006).
[12] ‘Do hedge fund managers have stock-picking skills?’ (2009).
[13] From ‘Blink: The power of thinking without thinking’ (2007).
[14] From ‘The Talent Code: Greatness isn’t born. It’s grown’ (2010).
[15] ‘Prospect Theory’ Kahneman and Tversky (1979).
[16] ‘The role of category accessibility in the interpretation of information’ Srull and Wyer (1979)
[17] Availability: The heuristic for judging frequency and probability’ (1973).
[18] From ‘Outliers’ (2008).
[19] Source ‘Winning the Losers Game’ Charles Ellis (1975).

Important Information

This material is communicated by GLG Partners LP (‘GLG’), a member of Man Group plc. GLG is authorised and regulated by the Financial Services Authority (‘FSA’).

Opinions expressed are those of the authors and may not be shared by all personnel of Man Group plc (‘Man’). These opinions are subject to change without notice. This material is for information purposes only and does not constitute an offer or invitation to make an investment in any financial instrument or in any product to which any member of Man’s group of companies provides investment advisory or any other services.


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